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Andres Monroy-Hernandez

Publications and source records attributed to Andres Monroy-Hernandez.

6 recordsLinked to original sources

Practicing a Second Language Without Fear: Mixed Reality Agents for Interactive Group Conversation

Developing speaking proficiency in a second language can be cognitively demanding and emotionally taxing, often triggering fear of making mistakes or being excluded from larger groups. While current learning tools show promise for speaking practice, most focus on dyadic, scripted scenarios, limiting opportunities for dynamic group interactions. To address this gap, we present ConversAR, a Mixed Reality system that leverages Generative AI and XR to support situated and personalized group conversations. It integrates embodied AI agents, scene recognition, and generative 3D props anchored to real-world surroundings. Based on a formative study with experts in language acquisition, we developed and tested this system with a user study with 21 second-language learners. Results indicate that the system enhanced learner engagement, increased willingness to communicate, and offered a safe space for speaking. We discuss the implications for integrating Generative AI and XR into the design of future language learning applications.

cs.HC

Botivist: Calling Volunteers to Action Using Online Bots

To help activists call new volunteers to action, we present Botivist: a platform that uses Twitter bots to find potential volunteers and request contributions. By leveraging different Twitter accounts, Botivist employs different strategies to encourage participation. We explore how people respond to bots calling them to action using a test case about corruption in Latin America. Our results show that the majority of volunteers (>80%) who responded to Botivist's calls to action contributed relevant proposals to address the assigned social problem. Different strategies produced differences in the quantity and relevance of contributions. Some strategies that work well offline and face-to-face appeared to hinder people's participation when used by an online bot. We analyze user behavior in response to being approached by bots with an activist purpose. We also provide strong evidence for the value of this type of civic media, and derive design implications.

cs.SI

Storia: Summarizing Social Media Content based on Narrative Theory using Crowdsourcing

People from all over the world use social media to share thoughts and opinions about events, and understanding what people say through these channels has been of increasing interest to researchers, journalists, and marketers alike. However, while automatically generated summaries enable people to consume large amounts of data efficiently, they do not provide the context needed for a viewer to fully understand an event. Narrative structure can provide templates for the order and manner in which this data is presented to create stories that are oriented around narrative elements rather than summaries made up of facts. In this paper, we use narrative theory as a framework for identifying the links between social media content. To do this, we designed crowdsourcing tasks to generate summaries of events based on commonly used narrative templates. In a controlled study, for certain types of events, people were more emotionally engaged with stories created with narrative structure and were also more likely to recommend them to others compared to summaries created without narrative structure.

cs.HC

Tag Me Maybe: Perceptions of Public Targeted Sharing on Facebook

Social network sites allow users to publicly tag people in their posts. These tagged posts allow users to share to both the general public and a targeted audience, dynamically assembled via notifications that alert the people mentioned. We investigate people's perceptions of this mixed sharing mode through a qualitative study with 120 participants. We found that individuals like this sharing modality as they believe it strengthens their relationships. Individuals also report using tags to have more control of Facebook's ranking algorithm, and to expose one another to novel information and people. This work helps us understand people's complex relationships with the algorithms that mediate their interactions with each another. We conclude by discussing the design implications of these findings.

cs.SI

Mixsourcing: a remix framework as a form of crowdsourcing

In this paper, we introduce the concept of mixsourcing as a modality of crowdsourcing focused on using remixing as a framework to get people to perform creative tasks. We explore this idea through the design of a system that helped us identify the promises and challenges of this peer-production modality.

cs.HC

Whoo.ly: Facilitating Information Seeking For Hyperlocal Communities Using Social Media

Social media systems promise powerful opportunities for people to connect to timely, relevant information at the hyper local level. Yet, finding the meaningful signal in noisy social media streams can be quite daunting to users. In this paper, we present and evaluate Whoo.ly, a web service that provides neighborhood-specific information based on Twitter posts that were automatically inferred to be hyperlocal. Whoo.ly automatically extracts and summarizes hyperlocal information about events, topics, people, and places from these Twitter posts. We provide an overview of our design goals with Whoo.ly and describe the system including the user interface and our unique event detection and summarization algorithms. We tested the usefulness of the system as a tool for finding neighborhood information through a comprehensive user study. The outcome demonstrated that most participants found Whoo.ly easier to use than Twitter and they would prefer it as a tool for exploring their neighborhoods.

cs.HC